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README.md
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---
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library_name: peft
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tags:
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- trl
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- dpo
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- generated_from_trainer
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base_model: Weni/WeniGPT-Agents-Mistral-1.0.6-SFT-merged
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model-index:
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- name: WeniGPT-Agents-Mistral-1.0.6-SFT-1.0.5-DPO
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# WeniGPT-Agents-Mistral-1.0.6-SFT-1.0.5-DPO
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This model is a fine-tuned version of [Weni/WeniGPT-Agents-Mistral-1.0.6-SFT-merged](https://huggingface.co/Weni/WeniGPT-Agents-Mistral-1.0.6-SFT-merged) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4260
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- Rewards/chosen: 0.9172
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- Rewards/rejected: -0.6078
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- Rewards/accuracies: 0.4643
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- Rewards/margins: 1.5251
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- Logps/rejected: -103.4404
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- Logps/chosen: -46.9008
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- Logits/rejected: -1.8652
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- Logits/chosen: -1.8327
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-06
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- train_batch_size: 2
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- eval_batch_size: 2
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- seed: 42
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 4
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.03
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- training_steps: 366
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
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|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
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| 0.6635 | 0.49 | 30 | 0.6524 | 0.0904 | 0.0036 | 0.4643 | 0.0867 | -97.3259 | -55.1696 | -1.8044 | -1.7832 |
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| 0.6026 | 0.98 | 60 | 0.5891 | 0.2506 | 0.0024 | 0.4643 | 0.2482 | -97.3380 | -53.5672 | -1.8099 | -1.7878 |
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| 0.5387 | 1.46 | 90 | 0.5295 | 0.4396 | -0.0275 | 0.4643 | 0.4671 | -97.6369 | -51.6775 | -1.8181 | -1.7943 |
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| 0.6033 | 1.95 | 120 | 0.4960 | 0.5751 | -0.0659 | 0.4643 | 0.6410 | -98.0210 | -50.3219 | -1.8261 | -1.8009 |
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| 0.5042 | 2.44 | 150 | 0.4709 | 0.6967 | -0.1479 | 0.4643 | 0.8446 | -98.8407 | -49.1060 | -1.8331 | -1.8059 |
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| 0.5087 | 2.93 | 180 | 0.4542 | 0.7878 | -0.2428 | 0.4643 | 1.0306 | -99.7900 | -48.1955 | -1.8425 | -1.8136 |
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| 0.4874 | 3.41 | 210 | 0.4428 | 0.8442 | -0.3560 | 0.4643 | 1.2002 | -100.9220 | -47.6315 | -1.8520 | -1.8219 |
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| 0.4229 | 3.9 | 240 | 0.4358 | 0.8750 | -0.4390 | 0.4643 | 1.3140 | -101.7521 | -47.3229 | -1.8575 | -1.8266 |
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| 0.5295 | 4.39 | 270 | 0.4313 | 0.9026 | -0.4960 | 0.4643 | 1.3986 | -102.3219 | -47.0471 | -1.8607 | -1.8289 |
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| 0.5466 | 4.88 | 300 | 0.4291 | 0.9119 | -0.5384 | 0.4643 | 1.4503 | -102.7461 | -46.9544 | -1.8629 | -1.8309 |
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| 0.4339 | 5.37 | 330 | 0.4268 | 0.9152 | -0.5900 | 0.4643 | 1.5052 | -103.2623 | -46.9216 | -1.8644 | -1.8320 |
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| 0.5438 | 5.85 | 360 | 0.4260 | 0.9172 | -0.6078 | 0.4643 | 1.5251 | -103.4404 | -46.9008 | -1.8652 | -1.8327 |
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### Framework versions
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- PEFT 0.10.0
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- Transformers 4.38.2
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- Pytorch 2.1.0+cu118
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- Datasets 2.18.0
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- Tokenizers 0.15.2
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